Measure & Analyze Applications Accelerated with Intel GPUs
Speakers: Xiaozhu Meng & Aaron Cherian, Rice University
HPC Kit from Rice University is an integrated suite of tools for measurement and analysis of program performance on computers that range from multicore desktop systems to the nation’s largest supercomputers. By using statistical sampling of timers and hardware performance counters, HPC Kit collects accurate measurements of a program’s work, resource consumption, and inefficiency, and attributes them to the full calling context in which they occur. HPC Kit supports measurement and analysis of serial codes, threaded codes (for example, pthreads or OpenMP), MPI, and hybrid (MPI + threads) parallel codes. With the prevalence of using GPU as an accelerator for scientific computation, we are extending HPC Kit to support applications accelerated with GPUs from several vendors. In this presentation, we discuss our recent development for supporting Intel® GPUs and our experience of profiling several applications porting to Intel GPUs using Data Parallel C++.
Calling all C++, DPC++, and CUDA developers. We’re searching for the next oneAPI hero—someone who can write code that will run on the latest CPUs, GPUs, and FPGAs. Submit your best projects to win some amazing prizes.
Supercomputing 2020 (SC20) Recorded Sessions on oneAPI
- C++ for Heterogeneous Programming: oneAPI
- Performance Tuning with the Roofline Model on GPUs and CPUs
- Panel: The oneAPI Software Abstraction for Heterogeneous Computing
Product and Performance Information
Performance varies by use, configuration and other factors. Learn more at www.Intel.com/PerformanceIndex.